Dynamic System Simulation Using Distributed Computation Hardware

Author(s):  
Keith A. Williams

The availability of low-cost, readily programmable digital hardware offers numerous opportunities for novel modeling and control approaches. One such opportunity is the realization of hardware modeling of distributed dynamic systems. Such models could be useful for control algorithms that require high-fidelity models operating in real-time. The ultimate goal is to utilize digital systems with programmable hardware. As a proof-of-concept, multiple discrete microcontrollers have been used to emulate how programmable hardware devices may be used to simulate a distributed vibrating system. Specifically, each microcontroller is treated as a single vibrating mass with stiffness and damping coupling between the masses. Each microcontroller has associated position and velocity variables. The only additional knowledge required to compute the acceleration of each “mass” is thus the position and velocity of each immediate neighboring mass/microcontroller. The computation time is independent of the number of nodes; adding nodes results in no reduction in processing speed. Consequently, the computational approach will be applicable to very high order models. Practical implementation of such models will require digitally programmable hardware such as field-programmable gate arrays (FPGA), however an added benefit will be a still greater reduction in cost, as multiple microcontrollers are replaced by a single FPGA. It is expected that the hardware modeling approach described in this work will have application not only in the field of vibration modeling and control, but also in other fields where control of distributed dynamic systems is desired.

2007 ◽  
Vol 31 (1) ◽  
pp. 127-141
Author(s):  
Yonghong Tan ◽  
Xinlong Zhao

A hysteretic operator is proposed to set up an expanded input space so as to transform the multi-valued mapping of hysteresis to a one-to-one mapping so that the neural networks can be applied to model of the behavior of hysteresis. Based on the proposed neural modeling strategy for hysteresis, a pseudo control scheme is developed to handle the control of nonlinear dynamic systems with hysteresis. A neural estimator is constructed to predict the system residual so that it avoids constructing the inverse model of hysteresis. Thus, the control strategy can be used for the case where the output of hysteresis is unmeasurable directly. Then, the corresponding adaptive control strategy is presented. The application of the novel modeling approach to hysteresis in a piezoelectric actuator is illustrated. Then a numerical example of using the proposed control strategy for a nonlinear system with hysteresis is presented.


Author(s):  
L. G. Barajas ◽  
A. Kansal ◽  
A. Saxena ◽  
M. Egerstedt ◽  
A. Goldstein ◽  
...  

Author(s):  
Scott Manwaring ◽  
Andrew Alleyne

Previous work has found benefit in using dimensional analysis in the modeling and control of dynamic systems. What has not been explored is how multiple dimensionless dynamic systems would interconnect and interact with one another. This work presents an initial investigation into the interconnection of dimensionless dynamic systems, including an analysis of the differences between interconnecting dimensioned and dimensionless systems. A strategy is developed to interconnect dimensionless dynamic systems and explored using models of multiple fluid power components. The interconnection strategy is tested through controller design and simulation, which reveals insight into the dimensionless transformation of the original dynamic systems.


Author(s):  
Melody L. Baglione

The Cooper Union is developing a new simultaneous lecture and laboratory approach to address the pedagogical challenge of finding the appropriate balance between theory and hands-on experimentation in teaching dynamic systems and control concepts. The new approach dedicates one hour each week to laboratory experiments with the class subdivided into small student groups having greater faculty interaction. Bench top experiments from National Instruments and Quanser include DC motor and inverted pendulum modeling and control workstations. Process control test rigs from Feedback Inc. include level, flow, temperature, and pressure control trainers. Devoting significant time to laboratory experiments gives students the opportunities to fully appreciate feedback control concepts and to acquire valuable practical skills. This paper discusses the new instructional approach, preliminary results, lessons learned, and future plans for improving the systems and control curriculum.


Author(s):  
Nael Barakat ◽  
Hugh Jack

Most engineering products nowadays are multi-part integrated systems that are produced by teams of engineers. These systems are characterized by their complexity and diversity of components that range between being fully mechanical to being fully electrical components. A vital aspect in successfully building and running of these systems is the proper modeling and control of their dynamics. As mechanical engineering students graduate and face this reality, a hands-on preparation to deal with similar systems during college experience becomes very rewarding. The important elements of applying knowledge in dynamic systems modeling and control are practiced during the laboratory session in college. At the Grand Valley State University (GVSU) School of Engineering (SOE) the integration of electrical, mechanical and software systems is instructed and practiced in a required course (EGR 345) entitled "Dynamic systems Modeling and Control." This course includes a theoretical part where principles of system dynamics, system components, and system control are emphasized. The course capitalizes on students' previous knowledge of the simple isolated systems and modifies their strategies and approach to look and treat engineering systems as complete integrated entities. In addition, the course includes a significant lab component and a major project through which the student gains vital hands-on experience. In this paper, the philosophy and major components of the course are discussed. The focus is on presenting a sequence of lab experiments that serve the application of principles of dynamic systems modeling and control, as well as the final project. These experiments are characterized by its comprehensiveness and cost effectiveness. Moreover, an innovative method of making the lab equipment available to the students, and mostly owned by them, will also be summarized. As this approach minimizes the financial burden of the lab equipment, it also gives the students an element of ownership and comfort dealing with equipment they own and use. As a matter of fact, it ultimately leads to the utilization of these pieces of equipment in an innovative way to produce an engineering electromechanical system that will perform the tasks required by their final project description. A discussion on the pros and cons in the outcomes of this approach and some modification plans for the next course offering will be provided at the end of the paper.


Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2574 ◽  
Author(s):  
Jesus Monroy-Anieva ◽  
Cyril Rouviere ◽  
Eduardo Campos-Mercado ◽  
Tomas Salgado-Jimenez ◽  
Luis Garcia-Valdovinos

This work describes the modeling, control and development of a low cost Micro Autonomous Underwater Vehicle (μ-AUV), named AR2D2. The main objective of this work is to make the vehicle to detect and follow an object with defined color by means of the readings of a depth sensor and the information provided by an artificial vision system. A nonlinear PD (Proportional-Derivative) controller is implemented on the vehicle in order to stabilize the heave and surge movements. A formal stability proof of the closed-loop system using Lyapunov’s theory is given. Furthermore, the performance of the μ-AUV is validated through numerical simulations in MatLab and real-time experiments.


Sign in / Sign up

Export Citation Format

Share Document